The present invention relates to a method and apparatus for analyzing and editing the morphology and time series relationships in electrocardiographic (ECG) signals.
The heart has a right side that circulates blood to the lungs for oxygenation and CO2 discharge and a left side that circulates oxygenated blood to the systemic circulatory vascular field of the body. Each side has an atrium that receives blood during relaxation of the heart muscle (diastole) and a ventricle that discharges blood when the heart muscle contracts (systole).
ECG signal data reflects the electrical activity of the heart conduction system and muscle in pumping blood through the lungs and systemic circulatory field of a subject. The signal contains a succession of waveforms produced by the repetitive action, or beating, of the heart. For a normal heart rate of about 60 to 80 beats per minute, the waveforms are produced about every 0.75 to 1 second or about every 750 to 1000 milliseconds.
A typical ECG waveform is shown in FIG. 1. It comprises a P wave, a QRS complex, and a T wave. The P wave is caused by the electric potentials generated when the atria of the heart depolarize before atrial contraction occurs. The QRS complex is caused by the potentials generated when the ventricles depolarize before their contraction and features the prominent R peak. As the contraction and pumping action of the heart occurs, repolarization of the heat muscle commences, slowly at first and then more rapidly as the ECG waveform concludes in the T wave, in some cases, in a U wave.
In addition to the presence and shape of the components of the ECG waveform (i.e. the morphology), the length of the components, and the spacing, or interval, between the components is useful in ECG interpretation. Commonly used intervals shown in FIG. 1 are the P-R interval, QRS duration, the ST-T segment, and the QT interval. The U wave, which is a slight depression in the S-T segment of the ECG waveform, believed to the attributable to late repolarization of certain parts of the heart may also be used.
The use of certain drugs, or combinations of drugs, can affect the ion channels of cardiac cells and is reflected in changes in the characteristics of ECG waveforms. An example of this is the use of drugs such as some anti-depressants and anti-retrovirals, that induce a prolongation of the QT interval. This prolongation can lead to a life threatening arrhythmia in the form of a ventricular tachycardia (excessive rapidity) termed “torsade de pointes”, often referred to simply as “torsade,” or TdP. Use of the QT interval is currently the only technique approved by regulatory authorities to predict possible drug induced TdP in clinical drug trials.
For this reason, efforts have been directed to obtaining a proper measurement of the QT interval, as well as accurate computation of a correction of the QT intervals of the ECG waveforms of a time series. This correction, QTc, is used to adjust the determination of the QT interval for changes in the heart rate. Previously, the QT interval was usually corrected based on an immediately previously occurring R-R interval. The R-R interval is the interval between the R peaks of successive waveforms. However, more and more research has shown that there could be some delay effects between R-R interval change and QT interval change. This delay effect, often also called “hysteresis,” can be as long as 2 minutes in some cases. But in most practical situations, only a short segment of ECG signal data, for example, 10 seconds of data, is available. It can make a large difference if different ECG beats are selected for the QTc calculation if there is some type of arrhythmia in the heart beat, as evidenced by an irregular R-R interval. Therefore, it is important to select a proper group of ECG beats for the QTc calculation within the available, short segment of ECG signal data.
Currently, in carrying out the measurement of the QT interval and QT correction (QTc), an amount of ECG signal is subjected to analysis using an ECG analysis algorithm to flag those ECG waveforms in the signal deemed suitable for QT interval and QTc measurement. The signal data is then reviewed by a cardiologist or other clinician who decides which waveforms to use for the QT interval measurement and QTc computation. While this selection is designed to improve the quality of data used to compute the QT quantities and improve the ultimate accuracy of the determination, at present, it is often an arduous task for the clinician.